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Detection of Collagenous Colitis Based on Histopathology Image Segmentation of Colon

Detection of Collagenous Colitis Based on Histopathology Ima...

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Iranian Machine Vision and Image processing (MVIP)

作者： Vahid Malekian Mojgan Mokhtari Saeid Sadri Rasoul Amirfattahi Alireza Aghaie Digital Signal Processing Research Laboratory Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran School of Medicine Isfahan University of Medical Sciences Isfahan Iran Isfahan University of Technology Isfahan Isfahan IR

Collagenous colitis is prevalent among pathological diseases. Because of normal radiological and endoscopic appearances, the microscopic image of colon tissue is necessary and important material for investigation of this disease. In this paper, a computerized system is developed for collagenous colitis diagnosis. First, colon tissues are colored with Mason trichrome to make sub-epithelial collagen band to be appeared in blue. Second, preprocessing is done on the microscopic image of colon tissue, and then Color histogram features in HSV color space and Haar Wavelet energy in detail coefficients of sub-band images are implemented to characterize the histological structure representation for tissue classification. KNN Classifier is selected for this classification, which segments the sub-epithelial collagen band from the image, and finally, thickness of sub-epithelial collagen band is determined by morphological operations. Abnormal case will be recognized if the thickness of sub-epithelial collagen band be more than 10 μm. Fifty clinical image samples were employed in the training and testing procedures for the evaluation of system performance. Through the applied classification it was revealed that collagenous colitis can be diagnosed accurately.

关键词： Microscopy Image color analysis Colon Feature extraction Image segmentation Training Histograms

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Universal Steganalysis Based on Local Prediction Error in Wavelet Domain

Universal Steganalysis Based on Local Prediction Error in Wa...

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International Conference on Intelligent Information Hiding and Multimedia Signal processing (IIHMSP)

作者： Anahita Shojaei-Hashemi Mostafa Mehdipour-Ghazi Shahrokh Ghaemmaghami Hamid Soltanian-Zadeh School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Electronics Research Institute Sharif University of Technology Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran

A passive universal image steganalysis method is proposed that is shown to be of higher detection accuracy than existing truly blind steganalysis methods including Farid's and the WAM. This is achieved by improving some weaknesses of Farid's steganalysis scheme in feature extraction, that is, instead of deriving an over-determined equation system for each sub band of the wavelet decomposition, the sub bands are divided into overlapping blocks and an over-determined equation system is constructed for each block. To guarantee the existence of finite answers, the over-determined equation systems are solved in a way different from Farid's by using Moore-Penrose pseudo-inverse concept. Further improvement to the performance is achieved by adding diagonal directions and increasing the number of moments. The comparative evaluations confirm the superiority of the proposed method over prevalent blind steganalysis schemes.

关键词： Equations Mathematical model Payloads Transform coding Correlation Educational institutions Reliability

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AASVMES: An intelligent expert system for realization of Adaptive Autonomy using Support Vector Machine

AASVMES: An intelligent expert system for realization of Ada...

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International Conference on Control, Instrumentation, and Automation

作者： N. Hassanpour M. A. Zamani A. Fereidunian H. Lesani Systems and Machines Research Laboratory (SMRL) Control and Intelligent Processing Center of Excellence (CIPCE) School of ECE University of Tehran Tehran Iran Electrical and Computer Engineering Department K. N. Toosi University of Technology Tehran Iran

We earlier introduced a novel framework for realization of Adaptive Autonomy (AA) in human-automation interaction (HAI). This study presents an expert system for realization of AA, using Support Vector Machine (SVM), referred to as Adaptive Autonomy Support Vector Machine Expert System (AASVMES). The proposed system prescribes proper Levels of Automation (LOAs) for various environmental conditions, here modeled as Performance Shaping Factors (PSFs), based on the extracted rules from the experts' judgments. SVM is used as an expert system inference engine. The practical list of PSFs and the judgments of GTEDC's (the Greater Tehran Electric Distribution Company) experts are used as expert system database. The results of implemented AASVMES in response to GTEDC's network are evaluated against the GTEDC experts' judgment. Evaluations show that AASVMES has the ability to predict the proper LOA for GTEDC's Utility Management Automation (UMA) system, which changes in relevance to the changes in PSFs; thus providing an adaptive LOA scheme for UMA.

关键词： Support vector machines Training Expert systems Complexity theory Automation Adaptive systems Humans

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Unscented transformation for depth from motion-blur in videos

Unscented transformation for depth from motion-blur in video...

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2010 IEEE computer Society Conference on computer Vision and Pattern Recognition - Workshops, CVPRW 2010

作者： Paramanand, C. Rajagopalan, A.N. Image Processing and Computer Vision Laboratory Department of Electrical Engineering Indian Institute of Technology Madras Chennai 600 036 India

ISBN: (纸本)9781424470297

In images and videos of a 3D scene, blur due to camera shake can be a source of depth information. Our objective is to find the shape of the scene from its motion-blurred observations without having to restore the original image. In this paper, we pose depth recovery as a recursive state estimation problem. We show that the relationship between the observation and the scale factor of the motion-blur kernel associated with the depth at a point is nonlinear and propose the use of the unscented Kalman filter for state estimation. The performance of the proposed method is evaluated on many examples. © 2010 IEEE.

关键词： State estimation

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Spectral clustering approach with sparsifying technique for functional connectivity detection in the resting brain

Spectral clustering approach with sparsifying technique for ...

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2010 International Conference on Intelligent and Advanced Systems, ICIAS 2010

作者： Ramezani, Mahdi Heidari, Amin Fatemizadeh, Emad Soltanian-Zadeh, Hamid Biomedical Signal and Image Processing Laboratory Sharif University of Technology Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI 48202 United States Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Iran

ISBN: (纸本)9781424466238

The aim of this study is to assess the functional connectivity from resting state functional magnetic resonance imaging (fMRI) data. Spectral clustering algorithm was applied to the realistic and real fMRI data acquired from a resting healthy subject to find functionally connected brain regions. In order to make computation of the spectral decompositions of the entire brain volume feasible, the similarity matrix has been sparsified with the t-nearestneighbor approach. Realistic data were created to investigate the performance of the proposed algorithm and comparing it to the recently proposed spectral clustering algorithm with the Nystrom approximation and also with some well-known algorithms such as the Cross Correlation Analysis (CCA) and the spatial Independent Component Analysis (sICA). To enhance the performance of the methods, a variety of data pre and post processing steps, including data normalization, outlier removal, dimensionality reduction by using wavelet coefficients, estimation of number of clusters and optimal number of independent components (ICs). Results demonstrate the applicability of the proposed algorithm for functional connectivity analysis.

关键词： Brain

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18th ACM International Conference on Multimedia ACM Multimedia 2010, MM'10

作者： Daras, Petros Semertzidis, Theodoros Makris, Lambros Strintzis, Michael G. Information Processing Laboratory Department of Electrical and Computer Engineering Aristotle University of Thessaloniki GR54124 Thessaloniki Greece Informatics and Telematics Institute Centre for Research and Technology Hellas GR57001 Thessaloniki Greece

ISBN: (纸本)9781605589336

Content searching and downloading are the two dominant actions of the Internet users today, despite the fact that the Internet was not originally architected to serve such actions. Content Centric Networking is the new trend in the research community to build network architectures that route content by name and not by the host's network address so as to efficiently deal with content persistence, availability and authenticity issues. In this work we propose an extension to the Content Centric Network protocol in order to support content search as a native process of the network. By using object descriptors to represent the actual content objects and integrate these descriptors in the network protocol we manage to search and retrieve content from the network not only by name but also by the content itself. In this approach, searching for information is a process distributed to the reachable network. Moreover, content aggregation is handled by the end user and not by content aggregation portals, thematic content search engines or information curators. By doing so, search is not any more an application but part of the network and can pave the way for many novel applications which have never been thought until today. © 2010 ACM.

关键词： Network architecture

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3D reconstruction of indoor and outdoor building scenes from a single image

3D reconstruction of indoor and outdoor building scenes from...

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2010 ACM Workshop on Surreal Media and Virtual Cloning, SMVC'10, Co-located with ACM Multimedia 2010

作者： Vouzounaras, Georgios Agapito, Juan Diego Perez-Moneo Daras, Petros Strintzis, Michael G. Department of Electrical and Computer Engineering Information Processing Laboratory Aristotle University of Thessaloniki GR54124 Thessaloniki Greece Centre for Research and Technology Informatics and Telematics Institute Hellas GR57001 Thessaloniki Greece

ISBN: (纸本)9781450301756

In this paper, a novel method is proposed able to automatically generate accurate 3D models of both outdoor buildings and indoor scenes with perspective cues from line segments that are automatically extracted from a single image with an uncalibrated camera. The proposed method uses geometric constraints and knowledge of photography and achieves an accurate, real-time and fully automated 3D reconstruction of the scene without any intervention from the user.

关键词： Three dimensional computer graphics

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Automatic segmentation of pallet images using the 2-D wavelet transform and YUV color space

Automatic segmentation of pallet images using the 2-D wavele...

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Iranian Conference on electrical engineering (ICEE)

作者： Aida Fooladivanda Narges Chehrerazi Saeed Sadri Rasoul Amirfattahi Mohammad Ali Montazeri Digital signal processing research Laboratory Department of Electrical and computer engineering Isfahan University of Technology Isfahan Iran

ISBN: (纸本)9781424467600

Segmentation is an important stage in automatic digital image processing. A special case of segmentation is to segment objects from their background. Among different segmentation algorithm for object detection, learning based approach is widely applied. In steel industry, pallets are moving on a rail. They have high resolution details in their structure and the image of a pallet taken by a camera in real time suffers from severe noise and illumination variations. The purpose of this paper is to segment the pallet from a frame of a sequence of video images, such that the pallet is segmented without degradation of resolution. We use the pallet image in YUV color space together with wavelet transform (WT) for detection. For classification Support Vector Machine (SVM) is incorporated to the images. It is shown that the above procedure segments the pallets successfully without degradation of resolution.

关键词： Image segmentation Wavelet transforms Image resolution Degradation Support vector machines Support vector machine classification Digital images Object detection Metals industry Rails

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A fast image registration algorithm for Digital Subtraction Angiography

A fast image registration algorithm for Digital Subtraction ...

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Iranian Conference of Biomedical engineering (ICBME)

作者： Mansour Nejati Rassoul Amirfattahi Saeed Sadri Digital Signal Processing Research Laboratory Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran

Digital Subtraction Angiography (DSA) is a powerful technique for the visualization of blood vessels. The major problem encountered in DSA images is the presence of motion artifacts which arise from the misalignment of successive images in the sequence. In this paper, a fast registration algorithm for coronary angiographic images is proposed. It involves a feature-based selection of control points for which the displacement is computed by means of template matching, and the complete displacement vector field is constructed by means of interpolation. To reduce the computational cost of the template matching procedure, an iterative hill-climbing approach is used for optimization and for handling the local misalignments, the image warping is performed based on multilevel B-spline interpolation.

关键词： Image edge detection Artificial neural networks Interpolation Pixel

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Online signature verification using combination of two classifiers

Online signature verification using combination of two class...

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Iranian Machine Vision and Image processing (MVIP)

作者： M. Saeidi R. Amirfattahi A. Amini M. Sajadi Digital Signal processing Research Laboratory Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran

The objective of signature verification is to distinguish forgery signature from genuine one. Online signature is the one which is registered through electronic devices such as digitizers and stored on computers in time sequence form. In this kind of signatures in addition to location information, time information such as speed and acceleration is stored. In this paper after accomplishment of some pre-processing procedures like normalization of signature size, smoothing and elimination of rotation on signatures using algorithms based on extremum matching of signals and ant colony, their time duration will be equalized. Afterwards, similarities between signatures will be determined using extended regression and finally will try to distinguish between forgery signatures from genuine one using support vector machine (SVM). The suggested online verification system is tested on SVC2004 signature set which is related to the first international signature verification competition and results are compared to respective results of participants. The results state that suggested method exhibits equal error rate (EER) of %4.3 in skilled forger group.

关键词： Forgery Mathematical model Equations Support vector machines Training Error analysis

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